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1. Efficient Prediction of Difficult Keyword Queries over Databases
Efficient Prediction of Difficult Keyword Queries over Databases
Keyword queries on databases provide easy access to data, but often suffer from low ranking
quality, i.e., low precision and/or recall, as shown in recent benchmarks. It would be useful to
identify queries that are likely to have low ranking quality to improve the user satisfaction. For
instance, the system may suggest to the user alternative queries for such hard queries. In this
paper, we analyze the characteristics of hard queries and propose a novel framework to measure
the degree of difficulty for a keyword query over a database, considering both the structure and
the content of the database and the query results. We evaluate our query difficulty prediction
model against two effectiveness benchmarks for popular keyword search ranking methods. Our
empirical results show that our model predicts the hard queries with high accuracy. Further, we
present a suite of optimizations to minimize the incurred time overhead.
 There have been collaborative efforts to provide standard benchmarks and evaluation
platforms for keyword search methods over databases. One effort is the data-centric track
of INEX WorkshopQueries were provided by participants of the workshop. Another
effort is the series of Semantic Search Challenges (SemSearch).The results indicate that
even with structured data, finding the desired answers tokeyword queries is still a hard
task. More interestingly, looking closer to the ranking quality of the best performing
methods on both workshops.
DISADVANTAGES OF EXISTING SYSTEM:
 Suffer from low ranking quality.
 Performing very poorly on a subset of queries.
 We set forth a principled framework and proposed novel algorithms to measure the
degree of the difficulty of a query over a DB, using the ranking robustness principle.
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ABSTRACT:
EXISTING SYSTEM:
PROPOSED SYSTEM:
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in

2. Efficient Prediction of Difficult Keyword Queries over Databases
 Based on our framework, we propose novel algorithms that efficiently predict the
effectiveness of a keyword query.
ADVANTAGES OF PROPOSED SYSTEM:
 Easily mapped to both XML and relational data.
 Higher prediction accuracy and minimize the incurred time overhead.
SYSTEM ARCHITECTURE:
SYSTEM REQUIREMENTS:
HARDWARE REQUIREMENTS:
 System : Pentium IV 2.4 GHz.
 Hard Disk : 40 GB.
 Floppy Drive : 1.44 Mb.
 Monitor : 15 VGA Colour.
 Mouse : Logitech.
 Ram : 512 Mb.
Contact: 9703109334, 9533694296
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in

3. Efficient Prediction of Difficult Keyword Queries over Databases
Contact: 9703109334, 9533694296
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in

4. Efficient Prediction of Difficult Keyword Queries over Databases
SOFTWARE REQUIREMENTS:
 Operating system : Windows XP/7.
 Coding Language : JAVA/J2EE
 IDE : Netbeans 7.4
 Database : MYSQL
Shiwen Cheng, Arash Termehchy, and Vagelis Hristidis,“Efficient Prediction of Difficult
Keyword Queries over Databases”,VOL. 26, NO. 6, JUNE 2014.
Contact: 9703109334, 9533694296
REFERENCE:
Email id: academicliveprojects@gmail.com, www.logicsystems.org.in